An information retrieval system uses terms and phrases to index, retrieve, organize and describe documents. Such information retrieval system may include a meta search engine, which may combine results of a plurality of search backends or services. When a user enters a search query in the search engine, the terms in the query are identified and used to retrieve documents from the plurality of search backends. For example, for a given search term, a search engine may return documents that are of the same type (e.g., only songs), or may also return documents that may be divided in a plurality of different logical corpora (e.g., for a given title, a meta search engine may return results that may include songs, books, videos, TV shows, etc. with the same title). The returned results may be ranked according to the individual logical corpus used in the search.
However, ranking of the individual corpus may be difficult since some corpora may be newly integrated (e.g., a newly integrated music search engine), with uneven usage patterns. Consequently, if a user performs a search of a music album title, the search results that are returned may include, for example, books with the same title, movies with the same title, and (in third place) music albums with the same title. In this regard, the result the user is most interested in will be displayed in third place instead of a first place. In this regard, an uneven usage pattern of one or more of the search backends within the meta search engine (e.g., using a very popular search backend or using a newly integrated search backend) can provide sub-optimal orderings of the final search results due to lack of appropriate levels of ranking data.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such approaches with some aspects of the present method and apparatus set forth in the remainder of this disclosure with reference to the drawings.